Upload app (1).py

app (1).py

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+from ssl import Options
+import joblib
+import pandas as pd
+import streamlit as st
+
+
+model = joblib.load('model.joblib')
+unique_values = joblib.load('unique_values(1).joblib')
+    
+
+#unique_post_on =  unique_values["Posted On"]
+unique_fea_1 = unique_values["fea_1"]
+unique_fea_2 = unique_values["fea_2"]
+unique_fea_3 = unique_values["fea_3"]
+unique_fea_4 = unique_values["fea_4"]
+unique_fea_5 = unique_values["fea_5"]
+unique_fea_6 = unique_values["fea_6"]
+unique_fea_7 = unique_values["fea_7"]
+unique_fea_8 = unique_values["fea_8"]
+unique_fea_9 = unique_values["fea_9"]
+unique_fea_10 = unique_values["fea_10"]
+unique_fea_11 = unique_values["fea_11"]
+
+
+def main():
+    st.title("Customer check risk")
+
+    with st.form("questionaire"):
+        fea1 = st.selectbox(options =unique_fea_1 )
+        fea3 = st.selectbox(options =unique_fea_3)
+        fea5 = st.selectbox(options =unique_fea_5 )
+        fea6 = st.selectbox(options =unique_fea_6 )
+        fea7 = st.selectbox(options =unique_fea_7 )
+        fea9 = st.selectbox(options =unique_fea_9 )
+
+        # clicked==True only when the button is clicked
+        clicked = st.form_submit_button("risk")
+        if clicked:
+            result=model.predict(pd.DataFrame({"fea1": [fea1],
+                                               "fea3": [fea3],                                               
+                                               "fea5": [fea5],
+                                               "fea6": [fea6],
+                                               "fea7": [fea7],
+                                               "fea9": [fea9]
+                                               }))
+            # Show prediction
+            if result==1:
+                result='the customer is in high credit risk'
+            else :
+                result='the customer is in low credit risk'
+            st.success('Your risk is '+result)
+# Run main()
+if __name__=='__main__':
+    main()